TUMCREATE is a research platform for the improvement of Singapore's public transportation, including the deployment of electric and autonomous mobility. Researchers from Technical University Munich and Nanyang Technological University join forces and are funded by Singapore’s National Research Foundation as part of the Campus for Research Excellence and Technological Enterprise (CREATE).
In TUMCREATE, over 100 scientists, researchers and engineers work together, led by Professors from the Technical University of Munich and Nanyang Technological University. The Mission of TUMCREATE is to seek the ultimate public transport system for the people of Singapore. Our innovative road transport solutions will provide high comfort and a positive travel experience, best protection of the environment and maximum benefit to the society and the economy.
The research group Electrification Suite & Test Lab (ESTL) in TUMCREATE puts an emphasis on the interaction of the electricity grid with advanced electrified public transport systems for Singapore. Ranging from charging infrastructure optimisation to demand side management and integration of renewable energies, ESTL covers many hierarchy levels of the electrification concept in the context of the major goals of TUMCREATE.
A research project has been established to study and implement various power efficient communication strategies in a network of IoT devices/sensor nodes. Modern IoT devices/sensors can operate in various power modes and configurations. However, these are not exploited for reducing the peak load when multiple devices are in use.
The goal of this master thesis / internship is to create a load balancing strategy to reduce peak load and overall power consumption in a decentralized network of devices.
The main tasks are:
explore various control optimization and scheduling strategies in literature to identify the state-of-the-art methods in this field.
Design and formulate a load balancing strategy with game theoretic/control theoretic optimization technique using device communication.
Add a scheduling algorithm that can exploit the optimization/learning from the communication to establish schedules for devices to operate.
Good knowledge of Embedded devices and communication protocols.
Very good C/C++/Python skills
Good knowledge on control theory and optimization techniques
Excellent interpersonal skills and communication skills in both written and spoken English and ability to work with people from different backgrounds and cultures
What we offer
Exposure to the state of the art research topics
An international and multidisciplinary working environment
Guidance by researchers from world-renowned universities
Opportunity for publishing in international journals and conferences
Multicultural and dynamic working atmosphere
Enquiries and How To Apply Please send your complete application including cover letter, CV, university transcripts and degree certificates to firstname.lastname@example.org.